Efficient routing strategy with transmission history information and its surrogate analysis

Akinori Yoshida, Yutaka Shimada and Takayuki Kimura

Physica A: Statistical Mechanics and its Applications, 2021, vol. 566, issue C

Abstract: Obtaining the optimum shortest paths for packets from their sources to destinations in communication networks is referred to as the packet routing problem. In a packet routing problem, the distribution of packets in the network always changes with time. Therefore, there is no guarantee that the shortest route at the current time is also the shortest one at the next time. For addressing these problems, a routing method using local transmission history information has already been proposed; this method shows effective performance. However, it is still unknown what kinds of topologies this method shows excellent performance for and how the transmission history information works to reduce packet congestion. To this end, we herein comprehensively evaluate the routing method using memory information. Numerical simulations clarify that the routing method using memory information shows excellent performance for heterogeneous type communication networks. Further, analysis of our method using surrogate data revealed that the transmission history information is useful for decentralizing packet congestion in communication networks.

Keywords: Complex networks; Routing problems; Nonlinear time-series analysis (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437120308955
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:566:y:2021:i:c:s0378437120308955

DOI: 10.1016/j.physa.2020.125597

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().